Abstract:Dynamic Line Rating is a technology devised to modify an overhead line's current-carrying capacity based on weather observation. The benefits of this modification may include reduced congestion costs, an increased renewable energy penetration rate, and improved network reliability. DLR is already well developed, but few papers in the literature investigate DLR day-ahead forecasting. The latter is central to DLR development since many of the decisions related to grid management are taken at least on a day-ahead… Show more
“…The cable temperature estimation is a widely addressed research area with applications in dynamic line rating [21], [22], [23] and lifetime estimation [24]. In addition to the thermal stress, there are models focused on the analysis of the joint influence of electrical and thermal stresses [17].…”
Power cables are critical assets for the reliable operation of the grid. The cable lifetime is generally estimated from the conductor temperature and associated lifetime reduction. However, these tasks are intricate due to the complex physicsof-failure (PoF) degradation mechanism of the cable. This is further complicated with the different sources of uncertainty that affect the cable lifetime estimation. Generally, simplified or deterministic PoF models are adopted resulting in non-accurate decision-making under uncertainty. In contrast, the integration of uncertainties leads to a probabilistic decision-making process impacting directly on the flexibility to adopt decisions. Accordingly, this paper presents a novel cable lifetime estimation framework that connects data-driven probabilistic uncertainty models with PoF-based operation and degradation models through Bayesian state-estimation techniques. The framework estimates the cable health state and infers confidence intervals to aid decision-making under uncertainty. The proposed approach is validated with a case study with different configuration parameters and the effect of measurement errors on cable lifetime are evaluated with a sensitivity analysis. Results demonstrate that ambient temperature measurement errors influence more than load measurement errors, and the greater the cable conductor temperature the greater the influence of uncertainties on the lifetime estimate.
“…The cable temperature estimation is a widely addressed research area with applications in dynamic line rating [21], [22], [23] and lifetime estimation [24]. In addition to the thermal stress, there are models focused on the analysis of the joint influence of electrical and thermal stresses [17].…”
Power cables are critical assets for the reliable operation of the grid. The cable lifetime is generally estimated from the conductor temperature and associated lifetime reduction. However, these tasks are intricate due to the complex physicsof-failure (PoF) degradation mechanism of the cable. This is further complicated with the different sources of uncertainty that affect the cable lifetime estimation. Generally, simplified or deterministic PoF models are adopted resulting in non-accurate decision-making under uncertainty. In contrast, the integration of uncertainties leads to a probabilistic decision-making process impacting directly on the flexibility to adopt decisions. Accordingly, this paper presents a novel cable lifetime estimation framework that connects data-driven probabilistic uncertainty models with PoF-based operation and degradation models through Bayesian state-estimation techniques. The framework estimates the cable health state and infers confidence intervals to aid decision-making under uncertainty. The proposed approach is validated with a case study with different configuration parameters and the effect of measurement errors on cable lifetime are evaluated with a sensitivity analysis. Results demonstrate that ambient temperature measurement errors influence more than load measurement errors, and the greater the cable conductor temperature the greater the influence of uncertainties on the lifetime estimate.
“…Under the conditions of the same ambient temperature and Al ball temperature, the forced convection heat transfer coefficients h f with different wind speeds and the natural convection heat transfer coefficient h 0 are firstly calculated according to (13), (14) and (17). Meanwhile, a variable err c is introduced to compare the difference between h 0 and h f , which is calculated by (19).…”
Section: Correlation Analysis Of Convective Heat Losses Between Al Bamentioning
confidence: 99%
“…According to the differences of monitoring data, the models of the DTR technology can be divided into two categories. The first type of DTR model, called the Weather model, calculates the conductor ampacity by directly monitoring all the weather data, including the ambient temperature, wind speed, wind direction and global solar irradiance [13,14]. A lot of sensors are needed to measure the weather data in Weather model [15].…”
With the increase in electricity demand, the ampacity calculation based on the dynamic thermal rating (DTR) technology is increasingly significant for assessing and improving the power transfer capacity of the existing overhead conductors. However, the DTR models now available present some inadequacies in measurement techniques related to wind speed. Therefore, it is essential to propose a new model instead of wind speed measuring in DTR technology. In this paper, the influence analysis of various weather parameters on the conductor ampacity is carried out by using the real weather data. Based on the analysis, it is confirmed that the impact of wind speed is significant, especially in the case of the low wind speed. Moreover, an equivalent heat transfer (EHT) model for DTR technology is proposed instead of wind speed measuring. For this EHT model, the calculation of conductor ampacity is realized through investigating the correlation of heat losses between the heating aluminum (Al) ball and conductor. Finally, combined with the finite element method (FEM), the EHT model proposed in this paper is verified by the Institute of Electrical and Electronic Engineers (IEEE) standard. The results indicate that the error of the EHT model is less than 6% when employing the steady thermal behavior of the Al ball to calculate the ampacity. The EHT model is useful in the real-time thermal rating of overhead conductors. It can increase the utilization of overhead conductors while also avoiding the limitation of the existing measurement techniques related to wind speed.
“…An analysis of the risk-based approach methodology in assessing of the OTL stability [21] as a probabilistic characteristic that determines normal power supply to consumers and similar researches [22]- [25] in the field of power grid reliability showed that traditional reliability targets such as SAIFI, SAIDI, EENS [26], LOLE, LOLH [27], [28] do not allow to fully evaluate and analyse the failure rate of power outages associated with climatic factors. These indices characterize the failure rate, the outage time without indicating the reason of accidents.…”
Section: Selection Of the Territory For Researchmentioning
In this study, the influence of climatic factors on overhead transmission lines reliability in Russia was discussed. A review of the possible impacts of climate change is provided. Using the example of an electric grid company providing electricity in the Republic of Bashkortostan some reliability targets associated with the impacts of weather events were calculated: the number of power outages, the failure rate of 1 km of overhead transmission lines and the outage time. From the calculations it was determined that these targets are at a quite high level, in particular for 6-10 kV overhead transmission lines. The main contribution is made by climatic factors wind and lighting storm. A correlation analysis of the overhead transmission lines outages as a function of the number of wind cases with a certain speed has shown a strong relationship between these characteristics. According to predictive information, the number of power outages in the territory under consideration in 2025 will increase by 1.5 times.
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